The present invention relates to a system and methods for a business tool for analyzing customer segments in a retail setting for the development of targeted and effective promotional activity. This business tool may be stand alone, or may be integrated into a pricing optimization system to provide more effective pricing of products. More particularly, the present customer analyzer system may identify and categorize customers into segments based upon customer attributes and behaviors. From these generated segments, promotional activity may be devised to produce a desired result, such as market share expansion, profit maximization, consumer behavior manipulation or some combination.
For a business to properly and profitably function, there must be decisions made regarding product pricing and promotional activity which, over a sustained period, effectively generates more revenue than costs incurred. In order to reach a profitable condition, the business is always striving to increase revenue while reducing costs.
One such method to increase revenue is via proper pricing of the products or services being sold. Additionally, the use of promotions may generate increased sales which aid in the generation of revenue. Likewise, costs may be decreased by ensuring that only required inventory is shipped and stored. Also, reducing promotion activity reduces costs. Thus, in many instances, there is a balancing between a business activity's costs and the additional revenue generated by said activity. The key to a successful business is choosing the best activities which maximize the profits of the business.
Choosing these profit maximizing activities is not always a clear decision. There may be no readily identifiable result to a particular activity. Other times, the profit response to a particular promotion may be counter intuitive. Thus, generating systems and methods for identifying and generating business activities which achieves a desired business result is a prized and elusive goal.
Currently, there are numerous methods of generating product pricing through demand modeling and comparison pricing. In these known systems, product demand and elasticity may be modeled to project sales at a given price. The most advanced models include cross elasticity between sales of various products. While these methods of generating prices and promotions may be of great use to a particular business, there are a number of problems with these systems. Primarily, these methods of pricing are reactive to historical transaction data. While some effort is made to increase consumer purchasing, these systems are less able to drive particular purchasing behaviors. Additionally, these systems treat the consumer as an aggregate entity. There is little granularity within the consumer base, thereby limiting the specificity of business activities to a particular group of the consumer base.
Returning to the basic principles of sound business management, that being increasing revenue while reducing costs, by introducing specificity of the consumer base in the generation of business decisions, a store may achieve more targeted (less cost) promotions which more effectively (increased revenue) influence the purchasing behaviors of the relevant consumers.
It is therefore apparent that an urgent need exists for improved analysis of customer segments. This improved customer segment analysis enables highly targeted promotions and more effective promotional activity. When coupled to a pricing optimization system, the customer segment analyzer may generate more finely tuned pricing for given products. This customer segment analyzer system provides businesses with an advanced competitive tool to greatly increase business profitability.